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The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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AI and productivity growth
Craig Piercycpiercy@ans.org
This month’s issue of Nuclear News focuses on supply and demand. The “supply” part of the story highlights nuclear’s continued success in providing electricity to the grid more than 90 percent of the time, while the “demand” part explores the seemingly insatiable appetite of hyperscale data centers for steady, carbon-free energy.
Technically, we are in the second year of our AI epiphany, the collective realization that Big Tech’s energy demands are so large that they cannot be met without a historic build-out of new generation capacity. Yet the enormity of it all still seems hard to grasp.
or the better part of two decades, U.S. electricity demand has been flat. Sure, we’ve seen annual fluctuations that correlate with weather patterns and the overall domestic economic performance, but the gigawatt-hours of electricity America consumed in 2021 are almost identical to our 2007 numbers.
J. Mao, V. Vishwakarma, Z. Welker, C. K. Tai, I. A. Bolotnov, V. Petrov, A. Manera
Nuclear Science and Engineering | Volume 198 | Number 7 | July 2024 | Pages 1404-1425
Research Article | doi.org/10.1080/00295639.2023.2241800
Articles are hosted by Taylor and Francis Online.
To provide computational fluid dynamics (CFD)–grade experimental data for studying stratification, measurements on the High-Resolution Jet (HiRJet) facility at the University of Michigan have been conducted with density differences of and , respectively. Fluid with a density different from the fluid initially present in the HiRJet tank was injected, and the propagation of the time-dependent density stratification was captured on a two-dimensional plane with the aid of the wire-mesh sensor technique for Reynolds numbers near 5000 and Richardson numbers near 0.29. Direct numerical simulations (DNSs) of the two cases have also been conducted to expand the multifidelity database. The novel experimental and DNS data were then used to assess the predictive capabilities of the Standard (SKE) model and the Reynolds Stress Transport (RST) model. In particular, the propagation speed and thickness of the stratification fronts were assessed by comparing the CFD results against the experimental and DNS data. It was found that the general trends of the stratified density fronts were well predicted by the CFD simulations; however, slight overprediction of the thickness of the stratification layer was found with the SKE model while the RST model gave a larger overprediction of the mixing. Examination of the turbulent statistics showed that the turbulent viscosity was largely overpredicted by the RST model compared to the SKE model.